matrix

问题 I'm trying to make a function with the arguments (a,tol=1e-8) that returns a boolean value that tells the user whether or not the matrix is symmetric (symmetric matrix is equal to its transpose). So far I have: def check_symmetric(a, tol=1e-8): if np.transpose(a, axes=axes) == np.transpose(a, axes=axes): return True def sqr(s): rows = len(s) for row in sq: if len(row) != rows: return False return True if a != sqr(s): raise ValueError although I keep getting an axes isn't defined message so I

问题 Suppose A is some square matrix. How can I easily exponentiate this matrix in R? I tried two ways already: Trial 1 with a for-loop hack and Trial 2 a bit more elegantly but it is still a far cry from A k simplicity. Trial 1 set.seed(10) t(matrix(rnorm(16),ncol=4,nrow=4)) -> a for(i in 1:2){a <- a %*% a} Trial 2 a <- t(matrix(c(0,1,0,0,0,0,1,0,0,0,0,1,0,0,0,0),nrow=4)) i <- diag(4) (function(n) {if (n<=1) a else (i+a) %*% Recall(n-1)})(10) 回答1: Although Reduce is more elegant, a for-loop

问题 This question already has answers here : How to vectorize this operation on every row of a matrix (3 answers) Closed 3 years ago . Given the following matrix: A B C [1,] TRUE FALSE TRUE [2,] FALSE TRUE TRUE [3,] FALSE FALSE TRUE [4,] FALSE TRUE TRUE [5,] FALSE TRUE TRUE [6,] TRUE TRUE TRUE m <- structure(c(TRUE, FALSE, FALSE, FALSE, FALSE, TRUE, FALSE, TRUE, FALSE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE), .Dim = c(6L, 3L), .Dimnames = list(NULL, c("A", "B", "C"))) How we can

问题 I am a little confused with Python's advanced slicing. I basically had a dictionary and with help from SO, I made it into an array. array1 = ([[[36, 16], [48, 24], [12, 4], [12, 4]], [[48, 24], [64, 36], [16, 6], [16, 6]], [[12, 4], [16, 6], [ 4, 1], [ 4, 1]], [[12, 4], [16, 6], [ 4, 1], [ 4, 1]]]) To practice using matrix solver, the array was turned into a square matrix (4 x 4) using: array_matrix_sized = array[:, :, 0] I read that this means [number of indices, rows, columns]. I am a

问题 I'm complitely new to Flood Fill algorithm. I checked it out from Wikipedia (http://en.wikipedia.org/wiki/Flood_fill). But didn't become that much wiser. I'm trying to use it in following situation. I have a matrix: matrix = [["a", "a", "b", "a", "a", "b"], ["a", "b", "b", "a", "b", "b"], ["b", "a", "b", "a", "a", "b"], ["b", "a", "b", "a", "b", "b"], ["a", "a", "b", "a", "a", "a"], ["a", "b", "b", "a", "a", "b"]] Then I let user to decide one point from matrix. If in that given point is "b"

问题 I have two columns, would like to retain only the non commutative rows.For the data below my output should contain one combination of (1 2). i.e. for my query (1 2) is same as (2 1). Is there a simple way to do it in R. Already tried transposing. and retaining the upper traingular matrix. but it becomes a pain re transposing back the data. A B prob 1 2 0.1 1 3 0.2 1 4 0.3 2 1 0.3 2 3 0.1 2 4 0.4 My final output should be: A B prob 1 2 0.1 1 3 0.2 1 4 0.3 2 3 0.1 2 4 0.4 回答1: We can use data

问题 I am looking for a fast and effective way to determine if vector B is Between the small angle of vector A and vector C. Normally I would use the perpendicular dot product to determine which sides of each line B lies on but in this case is not so simple because of the following: None of the vectors can be assumed to be normalized and normalizing them is an extra step I would prefer to avoid. I have no clear notion as to which side is the smallest angle so it is hard to say which side of the

问题 I have 3 points in a 3D space of which I know the exact locations. Suppose they are: (x0,y0,z0) , (x1,y1,z1) and (x2,y2,z2) . Also I have a camera that is looking at these 3 points and I know the 2D locations of those three points on camera view plane. So for example (x0,y0,z0) will be (x0',y0') , and (x1,y1,z1) will be (x1',y1') and (x2,y2,z2) will be (x2',y2') from the camera's point of view. What is the easiest way to find the projection matrix that will project those 3D points into 2D

问题 I have 3 points in a 3D space of which I know the exact locations. Suppose they are: (x0,y0,z0) , (x1,y1,z1) and (x2,y2,z2) . Also I have a camera that is looking at these 3 points and I know the 2D locations of those three points on camera view plane. So for example (x0,y0,z0) will be (x0',y0') , and (x1,y1,z1) will be (x1',y1') and (x2,y2,z2) will be (x2',y2') from the camera's point of view. What is the easiest way to find the projection matrix that will project those 3D points into 2D

问题 I have 3 points in a 3D space of which I know the exact locations. Suppose they are: (x0,y0,z0) , (x1,y1,z1) and (x2,y2,z2) . Also I have a camera that is looking at these 3 points and I know the 2D locations of those three points on camera view plane. So for example (x0,y0,z0) will be (x0',y0') , and (x1,y1,z1) will be (x1',y1') and (x2,y2,z2) will be (x2',y2') from the camera's point of view. What is the easiest way to find the projection matrix that will project those 3D points into 2D